# DESIGN OF A GENERIC PATH PATH PLANNING SYSTEM - PowerPoint PPT Presentation

View by Category
Title:

## DESIGN OF A GENERIC PATH PATH PLANNING SYSTEM

Description:

### Wall following, Space filling curves, Splines,Topological maps, etc. ... Homogeneous, Heterogeneous. AILAB Path Planning Workgroup. 13. Characteristics of Domain ... – PowerPoint PPT presentation

Number of Views:25
Avg rating:3.0/5.0
Slides: 28
Provided by: kemalk
Category:
Tags:
Transcript and Presenter's Notes

Title: DESIGN OF A GENERIC PATH PATH PLANNING SYSTEM

1
DESIGN OF A GENERIC PATH PATH PLANNING SYSTEM
• AILAB
• Path Planning Workgroup

2
OUTLINE
• Path Planning Basics
• Current Implementations
• System Design
• Conclusion

3
PATH PLANNING BASICS
• Path
• Configuration
• Work Space
• Configuration Space (Cspace)
• Cell Decomposition
• Free, Obstacle, Unknown Space
• Dimension and Degrees of Freedom

4
Cell Decomposition
• Regular Grids
• Multiresolution Cells
• Trapezoidal Cells

5
• Generalized Voronoi Diagrams
• Visibility Graphs

6
Properties of Path Planners
• Dynamic vs. static
• Global vs. local
• Optimal vs. suboptimal
• Complete vs. heuristic
• Metric vs. topological

7
Classification of Obstacles
• Category of Obstacles from Arai et. al. Arai89,
28

8
Path Planning Techniques
• Reactive Methods
• Artificial Potential Fields
• Vector Field Histogram Method
• Graph Traversing Methods
• A Algorithm
• Best First / Breadth First / Greedy Search
• Wavefront Method
• Other Methods
• Wall following, Space filling curves,
Splines,Topological maps, etc.

9
Problems with MA-PP
• Possible problems of applying ordinary PP methods
to MAS are,
• Collisions,
• Problems with MA-PP are,
• Information exchange,

10
Approaches
• Cenralised All robots in one composite system.
• Find complete and optimum solution if exists.
• Use complete information
• - Exponential computational complexity w.r.t of
robots
• - Single point of failure
• Decoupled First generate paths for robots
(independently), then handle interactions.
• Proportional computation time w.r.t of robots
• Robust
• - Not complete

11
Improvements for MA-PP
• Priority assignment
• Aging
• Rule-Based methods
• Resource allocation
• Robot Groups
• Virtual dampers and virtual springs
• Assigning dynamic information to edges and
vertices
• ...

12
Characteristics of MAS
• According to Dudek et. al. Dudek96,53,
• Team Size 1, 2, limited, infinite
• Communication Range None, Near, Infinite
Tree, Graph
• Communication Bandwidth High, Motion related,
Low, Zero
• Team Composition Homogeneous, Heterogeneous

13
Characteristics of Domain
• Initial Information None, Partial, Complete
• Number of Targets 1, Many
• Target Available True (i.e. go to target), False
(i.e. explore for target)
• Stationary Targets True, False

14
Complexity of Path Planning
• In 3D work space finding exact solution is
NP-HARD. Xavier92, 54
• Path planning is PSPACE-HARD. Reif79,55
• The compexity increases exponentially with,
• Number of DOF Canny88, 9
• Number of agents

15
Imperfect solutions
• Used in case of compex problems,
• Approximation
• Probabilistic
• Heuristic
• Special cases

16
CURRENT IMPLEMENTATIONS
• Sampling Based Algorithms
• Incomplete, but efficient and practical
• Types
• Multiple Query
• Single Query

17
Multiple Query
• A map is generated for multiple queries
• Uniform sampling of C-free
• Local planner attempts connections
• Biased sampling

18
Single Query
• Suited for high dimensions
• Find a path as quick as possible
• RRTs
• Grow from an initial state
• RRT-Connect Grow from both initial and goal
• Expand by performing incremental motions

19
Demos
• Path Planning
• Different sampling methods
• Rapidly-exploring Random Trees (RRTs)
• RRT
• RRT-Connect

20
SYSTEM DESIGN
• Following slides are based on Lavelles Motion
Strategy Library, implemented in C

21
Overview
• MODULES
• Model
• Geom
• Problem
• Solver
• Scene
• Render
• Gui

22
Model
• Contain incremental simulators that model the
kinematics and dynamics of a variety of
mechanical systems. The methods allow planning
algorithms to compute the future system state,
given the current state, an interval of time, and
a control input applied over that interval.

23
Geom
• These define the geometric representations of all
obstacles in the world, and of each part of the
robot. The methods allow planning algorithms to
determine whether any of the robot parts are in
collision with each other or with obstacles in
the world. (PQP - the Proximity Query Package )

24
Problem
• This is an interface class to a planner, which
abstracts the designer of a planning algorithm
away from particular details such as collision
detection, and dynamical simulations. Each
instance of a problem includes both an instance
of Model and of Geometry. An initial state and
final state are also included, which leads to a
problem to be solved by a solver (typically a
planning algorithm).

25
Planner
• The most important module.
• Base for all path planners...

26
CONCLUSION
• Path planning is a challenging task with many
different applications.
• Each application may device its own path planning
strategy.
• A generic path planning library may provide
solution or guidelines for other path planners.
• ...

27
QUESTIONS?
• Thank you...
• kaplanke_at_boun.edu.tr
• fuatgeleri_at_gmail.com